Mjukvaruverktyg för loggning och analys avindustriella processer

This report discusses developing a software log tool for analysis of industrial processes. The target was to develop software that can help electro Engineers for monitor and fault finding in industrial processes. The tool is called PLS (Process log server), and is developed in Visual Studio.NET Framework 2005. PLS works as a client with Beijer Electronics OPC Server. The program is able to read data from PLC (Programmable Logic Controller), trough the OPC Server. PLS connects to all kind of controllers that is supported by the Beijer Electronics OPC Server. Signal data is stored in a database for later analysis. Chosen signals data can easily be exported into a text file. The text file is adopted for import to MS Office Excel. User manual [UM-07] is written as a separate document. The software acted stable through the function test. The final product becomes a first-rate tool that is simple to use. As an advantage, the software can be developed with more functions in the future.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Acupuncture with manual and electrical stimulation for labour pain : a longitudinal randomised controlled trial

Background: Acupuncture is commonly used to reduce pain during labour despite contradictory results. The aim of this study is to evaluate the effectiveness of acupuncture with manual stimulation and acupuncture with combined manual and electrical stimulation (electro-acupuncture) compared with standard care in reducing labour pain. Our hypothesis was that both acupuncture stimulation techniques were more effective than standard care, and that electro-acupuncture was most effective.  Methods: A longitudinal randomised controlled trial. The recruitment of participants took place at the admission to the labour ward between November 2008 and October 2011 at two Swedish hospitals. 303 nulliparous women with normal pregnancies were randomised to: 40 minutes of manual acupuncture (MA), electro-acupuncture (EA), or standard care without acupuncture (SC). Primary outcome: labour pain, assessed by Visual Analogue Scale (VAS). Secondary outcomes: relaxation, use of obstetric pain relief during labour and post-partum assessments of labour pain. The sample size calculation was based on the primary outcome and a difference of 15 mm on VAS was regarded as clinically relevant, this gave 101 in each group, including a total of 303 women.  Results: Mean estimated pain scores on VAS (SC: 69.0, MA: 66.4 and EA: 68.5), adjusted for: treatment, age, education, and time from baseline, with no interactions did not differ between the groups (SC vs MA: mean difference 2.6, 95% confidence interval [CI] -1.7-6.9 and SC vs EA: mean difference 0.6 [95% CI] -3.6-4.8). Fewer number of women in the EA group used epidural analgesia (46%) than women in the MA group (61%) and SC group (70%) (EA vs SC: odds ratio [OR] 0.35; [95% CI] 0.19-0.67).  Conclusions: Acupuncture does not reduce women's experience of labour pain, neither with manual stimulation nor with combined manual and electrical stimulation. However, fewer women in the EA group used epidural analgesia thus indicating that the effect of acupuncture with electrical stimulation may be underestimated. These findings were obtained in a context with free access to other forms of pain relief.